ComfyUI Node: Primere Visual LORA Selector

Primere Visual LORA Selector:

PrimereVisualLORA is a specialized node designed to enhance your AI art generation process by integrating LORA (Low-Rank Adaptation) models into your visual workflows. This node allows you to apply multiple LORA models to your base model, providing fine-tuned control over the visual style and characteristics of the generated images. By adjusting the weights and configurations of these LORA models, you can achieve a wide range of artistic effects and styles, making it a powerful tool for AI artists looking to customize and refine their outputs. The main goal of PrimereVisualLORA is to offer flexibility and precision in applying LORA models, enabling you to experiment with different visual styles and achieve the desired artistic results.

Primere Visual LORA Selector Input Parameters:

lora_4_model_weight

This parameter controls the weight of the fourth LORA model applied to the base model. The weight determines the influence of the LORA model on the final output, with higher values increasing its impact. The default value is 1.0, with a minimum of -10.0 and a maximum of 10.0, adjustable in steps of 0.01.

lora_4_clip_weight

This parameter adjusts the weight of the fourth LORA model applied to the CLIP (Contrastive Language-Image Pre-Training) model. Similar to the model weight, it influences the degree to which the LORA model affects the CLIP model's output. The default value is 1.0, with a range from -10.0 to 10.0, and can be adjusted in steps of 0.01.

use_lora_5

A boolean parameter that enables or disables the use of the fifth LORA model. When set to True, the fifth LORA model is applied; otherwise, it is ignored. The default value is False.

lora_5

This parameter specifies the fifth LORA model to be used. It is a list of available LORA models that you can select from.

lora_5_model_weight

This parameter controls the weight of the fifth LORA model applied to the base model. The default value is 1.0, with a minimum of -10.0 and a maximum of 10.0, adjustable in steps of 0.01.

lora_5_clip_weight

This parameter adjusts the weight of the fifth LORA model applied to the CLIP model. The default value is 1.0, with a range from -10.0 to 10.0, and can be adjusted in steps of 0.01.

use_lora_6

A boolean parameter that enables or disables the use of the sixth LORA model. When set to True, the sixth LORA model is applied; otherwise, it is ignored. The default value is False.

lora_6

This parameter specifies the sixth LORA model to be used. It is a list of available LORA models that you can select from.

lora_6_model_weight

This parameter controls the weight of the sixth LORA model applied to the base model. The default value is 1.0, with a minimum of -10.0 and a maximum of 10.0, adjustable in steps of 0.01.

lora_6_clip_weight

This parameter adjusts the weight of the sixth LORA model applied to the CLIP model. The default value is 1.0, with a range from -10.0 to 10.0, and can be adjusted in steps of 0.01.

use_lora_keyword

A boolean parameter that enables or disables the use of LORA keywords. When set to True, LORA keywords are used in the generation process. The default value is False.

lora_keyword_placement

This parameter determines the placement of LORA keywords in the prompt. Options are "First" or "Last," with the default being "Last."

lora_keyword_selection

This parameter specifies the method of selecting LORA keywords. Options are "Select in order" or "Random select," with the default being "Select in order."

lora_keywords_num

This parameter sets the number of LORA keywords to be used. The default value is 1, with a minimum of 1 and a maximum of 50, adjustable in steps of 1.

lora_keyword_weight

This parameter controls the weight of the LORA keywords. The default value is 1.0, with a range from 0 to 10.0, and can be adjusted in steps of 0.1.

Primere Visual LORA Selector Output Parameters:

model_lora

This output parameter provides the modified base model after applying the specified LORA models and weights. It reflects the cumulative effect of all the LORA adjustments, resulting in a model that generates images with the desired visual characteristics.

clip_lora

This output parameter provides the modified CLIP model after applying the specified LORA models and weights. It reflects the cumulative effect of all the LORA adjustments on the CLIP model, influencing the text-to-image generation process.

Primere Visual LORA Selector Usage Tips:

• Experiment with different LORA model weights to find the optimal balance for your desired visual style.
• Use the lora_keyword_placement and lora_keyword_selection parameters to fine-tune how LORA keywords influence the generation process.
• Start with the default weights and gradually adjust them to see how each LORA model affects the output.

Primere Visual LORA Selector Common Errors and Solutions:

"LORA model not found"

• Explanation: This error occurs when the specified LORA model cannot be located in the designated folder.
• Solution: Ensure that the LORA model file is correctly named and placed in the appropriate directory.

"Invalid weight value"

• Explanation: This error occurs when a weight parameter is set outside the allowed range.
• Solution: Check the weight values and ensure they are within the specified range (-10.0 to 10.0).

"Keyword selection method not recognized"

• Explanation: This error occurs when an invalid keyword selection method is specified.
• Solution: Verify that the lora_keyword_selection parameter is set to either "Select in order" or "Random select".